Impact of COVID-19 on critical care research

This report summarizes the results of an ongoing study focused on understanding the impact of the COVID-19 pandemic on Critical Care research. It includes data submitted by 126 centres between 2020-03-23 and 2020-07-14.

Participating centres

---

ICU location

map_world

Country	ICUs
CAN	37
USA	30
AUS	21
FRA	5
NLD	5
NZL	4
ARG	2
GBR	2
IDN	2
ITA	2
MEX	2
SGP	2
THA	2
BRA	1
COL	1
DNK	1
ECU	1
IND	1
LBN	1
MYS	1
PAK	1
URY	1
VNM	1

---

ICU population

dat_redcap %>% 
  select(record_id, site_pop) %>% 
  drop_na(site_pop) %>% 
  mutate(site_pop = recode(site_pop, "1" = "Adult", "2" = "Pediatric", "3" = "Mixed")) %>% 
    count(site_pop) %>% 
  mutate(perc = n.per(n, sum(n), 0),
         label = paste(site_pop, "\n", perc, sep = "")
         ) %>% 
  mutate(order = row_number(),
         fraction = n / sum(n),
         label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>% 
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
  geom_col(position = "fill", width = 1) +
  geom_text(aes(label = label, y = label_pos, hjust = "outward"), 
            lineheight = 0.9, x = 2.75, size = 4) +
  coord_polar("y", start = 0, clip = "off") +
  scale_fill_brewer(palette = "Paired")+
  scale_x_continuous(limits = c(0.05, 2.5))+
  theme_void()+
  theme(legend.position = "none")

---

Centre type

dat_redcap %>% 
  select(record_id, site_setting) %>% 
  drop_na(site_setting) %>% 
  mutate(site_setting = recode(site_setting, "1" = "Academic", "2" = "Community")) %>% 
    count(site_setting) %>% 
  mutate(perc = n.per(n, sum(n), 0),
         label = paste(site_setting, "\n", perc, sep = "")
         ) %>% 
  mutate(order = row_number(),
         fraction = n / sum(n),
         label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>% 
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
  geom_col(position = "fill", width = 1) +
  geom_text(aes(label = label, y = label_pos, hjust = "outward"), 
            lineheight = 0.9, x = 2.75, size = 4) +
  coord_polar("y", start = 0, clip = "off") +
  scale_fill_brewer(palette = "Accent")+
  scale_x_continuous(limits = c(0.05, 2.5))+
  theme_void()+
  theme(legend.position = "none")

---

Surveys per month

dat_redcap %>%
  select(redcap_event_name) %>%
  filter(redcap_event_name != "centre_info_arm_1") %>%
  mutate(Month = case_when(
    redcap_event_name == "202003_arm_1" ~ "March",
    redcap_event_name == "202004_arm_1" ~ "April",
    redcap_event_name == "202005_arm_1" ~ "May",
    redcap_event_name == "202006_arm_1" ~ "June"
  )) %>%
  mutate(Month = fct_relevel(Month, c("March", "April", "May", "June"))) %>%
  group_by(Month) %>%
  drop_na() %>%
  tally() %>%
  select(Month, "Count" = n) %>%
  kable()

Month	Count
March	107
April	104
May	101
June	91

# weekly_demo %>%  
#   kable()

---

COVID-19

---

Are there any patients in your hospital with CONFIRMED COVID-19? (n = 401 surveys)

ggplot(monthly_covid_hosp) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_hosp), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_hosp$xcenter, labels = monthly_covid_hosp$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Are there any patients in your ICU with CONFIRMED COVID-19? (n = 401 surveys)

ggplot(monthly_covid_icu) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_icu), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_icu$xcenter, labels = monthly_covid_icu$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Is your ICU currently enrolling patients in any COVID-19 specific studies? (n = 394 surveys)

ggplot(monthly_res_covid_any) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_res_covid_any$xcenter, labels = monthly_res_covid_any$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

What types of COVID-19 specific research studies are currently enrolling patients in your ICU? (n = 402 surveys) (Question added after start of the study)

dat_redcap %>% 
  filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
  mutate(Month = recode(redcap_event_name, 
                        "202003_arm_1" = "March 2020", 
                        "202004_arm_1" = "April 2020", 
                        "202005_arm_1" = "May 2020",
                        "202006_arm_1" = "June 2020"),
         Month = fct_inorder(Month)) %>%
  select(Month, "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
  mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
  group_by(Month) %>%
  summarise_at(c("Randomized", "Non-randomized", "Observational", "Other"),sum, na.rm= TRUE)%>%
  kable(align = "c")

Month	Randomized	Non-randomized	Observational	Other
March 2020	14	1	25	1
April 2020	26	12	58	3
May 2020	39	14	68	2
June 2020	30	8	61	4

#This is the code I have trial but I am stuck here
#dat_redcap %>% 
 #filter(redcap_event_name != "centre_info_arm_1") %>%
  #mutate(Month = recode(redcap_event_name, 
                        #"202003_arm_1" = "March 2020", 
                        #"202004_arm_1" = "April 2020", 
                        #"202005_arm_1" = "May 2020",
                        #"202006_arm_1" = "June 2020"),
        #Month = fct_inorder(Month)) %>%
  #select(Month, record_id,  "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
  #mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
  #mutate("Site Count" = case_when(
    #Randomized == 1 | `Non-randomized` == 1 | Observational == 1 | Other == 1 ~ 1,
    #TRUE ~ 0
  #)) %>%
  #group_by(Month) %>%
  #summarise_at(c("Randomized", "Non-randomized", "Observational", "Other", "Site Count"),sum, na.rm= TRUE)
#Comments
#dat_redcap %>% 
  #select(Other = res_cov_type_other) %>% 
  #drop_na(Other) %>% 
  #kable()

---

Is your ICU currently preparing for any COVID-19 specific studies? (Question added after start of the study)

ggplot(monthly_res_covid_any_prep) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any_prep), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_res_covid_any_prep$xcenter, labels = monthly_res_covid_any_prep$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

Institutional policies

---

Is your REB/IRB prioritizing approval or willing to expedite approval of COVID-19 protocols? (n = 402 surveys)

ggplot(monthly_covid_reb) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_reb), 
            colour = "white", size = 2) +
  scale_fill_manual(name = "", values = c("#F7977A", "#FFF79A", "#82CA9D"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_reb$xcent, labels = monthly_covid_reb$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

# #require suspending enrolment in icu studies
# dat_redcap %>% 
#   filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
#   mutate(Month = recode(redcap_event_name, 
#                         "202003_arm_1" = "March 2020", 
#                         "202004_arm_1" = "April 2020", 
#                         "202005_arm_1" = "May 2020",
#                         "202006_arm_1" = "June 2020"),
#          Month = fct_inorder(Month)) %>%
#   select(Month, "Yes - All studies" = policy___1, "Yes - All non-COVID-19 studies" = policy___2 , "Yes - Some studies" = policy___3, "No" = policy___4, "Other" = policy___5) %>%
#   mutate_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"), 
#             as.numeric) %>%
#   group_by(Month) %>%
#   summarise_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"),sum, na.rm= TRUE) %>%
#   kable(align = "c")
#TABLE FOR THIS QUESTION
#Types of Studies that were affected?
#dat_redcap %>% 
  #select(Comments = policy_some_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()
#Please explain the other requirements
#dat_redcap %>% 
  #select(Comments = policy_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Impact on research

---

Because of COVID-19 or preparation for it, has your ICU:

Suspended recruitment for any studies? (n = 402 surveys)

ggplot(monthly_effect_suspend) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_suspend), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_suspend$xcent, labels = monthly_effect_suspend$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#dat_redcap %>% 
  #select(Comments = effect_suspend_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Modified recruitment for current studies? (n = 401 surveys)

ggplot(monthly_effect_modify) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_modify), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_modify$xcent, labels = monthly_effect_modify$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_modify_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Delayed the initiation of new (non-COVID-19) studies? (n = 400 surveys)

ggplot(monthly_effect_delay) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_delay), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_delay$xcent, labels = monthly_effect_delay$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_delay_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Enrolled MORE patients in studies because of increased patient volume? (n = 401 surveys)

ggplot(monthly_effect_more) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_more), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_more$xcent, labels = monthly_effect_more$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments ADD THIS BACK IN IF THERE ARE COMMENTS
#dat_redcap %>%
  #select(Comments = effect_more_explain) %>%
  #drop_na(Comments) %>%
  #kable()

---

Enrolled FEWER patients in studies because of increased patient volume? (n = 400 surveys)

ggplot(monthly_effect_less) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_less), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_less$xcent, labels = monthly_effect_less$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_less_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Changed the approach to co-enrollment in studies? (n = 400 surveys)

ggplot(monthly_effect_co) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_co), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_co$xcent, labels = monthly_effect_co$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_co_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Changed or stopped collection of biologic samples? (n = 400 surveys)

ggplot(monthly_effect_bio) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_bio), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_bio$xcent, labels = monthly_effect_bio$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_bio_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Other effects on studies in your ICU? (n = 388 surveys)

ggplot(monthly_effect_other_yn) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_other_yn), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_other_yn$xcent, labels = monthly_effect_other_yn$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

---

Reasons for impact

---

Because of COVID-19 or preparation for it, how much of an effect have the following had on research in your ICU?

Research staff WITH a clinical background are needed to work clinically (n = 401 surveys)

ggplot(monthly_reason_clinwork) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinwork$xcent, labels = monthly_reason_clinwork$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Research staff WITHOUT a clinical background are needed to help with hospital activities (n = 400 surveys)

ggplot(monthly_reason_work) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_work), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_work$xcent, labels = monthly_reason_work$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Investigators are needed to work clinically (n = 307 surveys) (Question added after start of the study)

ggplot(monthly_reason_clinwork_invest) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork_invest), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinwork_invest$xcent, labels = monthly_reason_clinwork_invest$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Research staff are concerned about their safety working during outbreak (n = 400 surveys)

ggplot(monthly_reason_safety) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_safety), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_safety$xcent, labels = monthly_reason_safety$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Your pediatric ICU is admitting (or planning to admit) adults (n = 185 surveys) (Question added after start of the study)

ggplot(monthly_reason_adults) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_adults), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_adults$xcent, labels = monthly_reason_adults$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

Error in grid.Call.graphics(C_setviewport, vp, TRUE) : 
  non-finite location and/or size for viewport

---

Not enough research staff for increased number of COVID-19 studies (n = 396 surveys)

ggplot(monthly_reason_numstudies) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numstudies), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_numstudies$xcent, labels = monthly_reason_numstudies$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Not enough research staff for increased number of eligible patients (n = 400 surveys)

ggplot(monthly_reason_numpts) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numpts), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_numpts$xcent, labels = monthly_reason_numpts$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Infection control policies limiting research staff access to the ICU (n = 399 surveys)

ggplot(monthly_reason_accessicu) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accessicu), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_accessicu$xcent, labels = monthly_reason_accessicu$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Infection control policies limiting research staff access to patients with confirmed or suspected COVID-19 (n = 400 surveys)

ggplot(monthly_reason_accesspt) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accesspt), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_accesspt$xcent, labels = monthly_reason_accesspt$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Clinical staff are too busy to complete research-related tasks (n = 400 surveys)

ggplot(monthly_reason_clinworkload) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinworkload), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinworkload$xcent, labels = monthly_reason_clinworkload$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

Research facilities for processing or storage of biological samples are closed or have reduced capacity (n = 341 surveys) (Question added after start of the study)

ggplot(monthly_reason_lab) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_lab), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_lab$xcent, labels = monthly_reason_lab$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

---

COVID-19 specific research is prioritized over other research (n = 398 surveys)

ggplot(monthly_reason_priorities) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_priorities), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_priorities$xcent, labels = monthly_reason_priorities$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#dat_redcap %>% 
  #select(Comments = reason_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

To join this study

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On behalf of the Canadian Critical Care Trials Group and Canadian Critical Care Research Coordinators group, we invite your site to participate in a short longitudinal survey of the effects of COVID-19 on critical care research.

Use this link to send us the name and email of the person who will complete the survey on behalf of your centre: http://bit.ly/3aNqo8Z
They’ll receive a separate email with the survey within 24 hours and will get:
1) A 3-question survey about your ICU
2) A short (<10 min) monthly survey about the impact of COVID-19 on research in your ICU

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About this study

Background: As we prepare for and manage COVID-19 patients in our ICUs, we realize both the importance of studying this disease and our role as global leaders in critical care research. From our experiences with SARS and H1N1, we also know that COVID-19 may both enhance and constrain current critical care research projects.

Objectives: The aims of this study are to:
1. Characterize current research activities in ICUs
2. Describe the effects of COVID-19 (and preparations) on research in ICUs, specifically to: identify new research started due to COVID-19; describe any impact on existing research activities; and identify COVID-19 hospital or ICU policies affecting research.

Methods: If you agree for your site to participate, you or your delegate will receive:
• A link to a single, brief survey (3 questions) about your ICU
• A link to a short (<10 minutes) survey about the impact of COVID-19 on research in your ICU. It will be sent on the first of the month for the duration of the COVID-19 outbreak.
• A report summarizing the results after each monthly survey

Ethics and privacy: This study has been reviewed by the Hamilton Integrated Research Ethics Board. Participation is of course voluntary and submitting data implies your consent to participate . You can stop participating at any time and prior to analysis you can withdraw any data from your centre. We will not publish any site or personal identifying information without your express consent.

Thank you, and we welcome any suggestions for adapting and updating this survey as events in this pandemic unfold.

Mark Duffett, RPh PhD
Departments of Pediatrics and Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada. duffetmc@mcmaster.ca, @M_Duffett

Michelle Kho, PT PhD
School of Rehabilitation Science, McMaster University, Hamilton, Canada. khome@mcmaster.ca, @khome